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20172022
most citedRetinaMask: Learning to predict masks improves state-of-the-art single-shot detection for free

119 citations · 132 across the 5 of their papers we have counts for

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5 papers · 1 filter

cs.CV20222 cited

Hydra Attention: Efficient Attention with Many Heads

Daniel Bolya, Cheng-Yang Fu, Xiaoliang Dai +2

While transformers have begun to dominate many tasks in vision, applying them to large images is still computationally difficult. A large reason for this is that self-attention sca…

cs.CV20221 cited

End-to-End Visual Editing with a Generatively Pre-Trained Artist

Andrew Brown, Cheng-Yang Fu, Omkar Parkhi +2

We consider the targeted image editing problem: blending a region in a source image with a driver image that specifies the desired change. Differently from prior works, we solve th…

cs.CV20192 cited

IMP: Instance Mask Projection for High Accuracy Semantic Segmentation of Things

Cheng-Yang Fu, Tamara L. Berg, Alexander C. Berg

In this work, we present a new operator, called Instance Mask Projection (IMP), which projects a predicted Instance Segmentation as a new feature for semantic segmentation. It also…

cs.CV2019119 cited

RetinaMask: Learning to predict masks improves state-of-the-art single-shot detection for free

Cheng-Yang Fu, Mykhailo Shvets, Alexander C. Berg

Recently two-stage detectors have surged ahead of single-shot detectors in the accuracy-vs-speed trade-off. Nevertheless single-shot detectors are immensely popular in embedded vis…

cs.CV2018

Target Driven Instance Detection

Phil Ammirato, Cheng-Yang Fu, Mykhailo Shvets +2

While state-of-the-art general object detectors are getting better and better, there are not many systems specifically designed to take advantage of the instance detection problem.…